Infrastructure Deployment Services Technical Consultant

What do you need to succeed in this opportunity

• Strong experience administering Linux environments (RHEL, Rocky Linux, Ubuntu, SLES) and supporting enterprise-scale HPC and AI infrastructure.
• Proven background in deploying, integrating, and supporting HPC and AI clusters, from installation through production readiness.
• Deep understanding of NVIDIA AI platforms and GPU architectures, including GB300 NVL72, NVLink, NVSwitch, GPU clustering, AI Factory concepts, and GPU resource management.
• Hands-on experience with high-performance networking technologies, including InfiniBand, Ethernet, RoCEv2, Spectrum-X, and fabric management.
• Solid expertise with Kubernetes, OpenShift, containerized workloads, GPU orchestration platforms, and AI/ML technologies such as Kubeflow, MLflow, JupyterHub, Run:AI, Rafay, ClearML, and MLOps solutions.
• Experience with HPC workload scheduling and resource management tools such as Slurm and PBS Pro, as well as deploying and integrating high-performance storage platforms including GPFS, VAST Data, and DDN.
• Strong knowledge of cluster provisioning, system bring-up, validation, benchmarking, acceptance testing, monitoring and observability tools (Grafana, Prometheus, Loki, Icinga, NVIDIA DCGM), and NVIDIA Cluster Validation Suite (CVS).
• Proficiency in Python, Bash, Ansible, and Git, combined with excellent troubleshooting, customer-facing, documentation, workshop delivery, knowledge transfer skills, and ideally certifications in NVIDIA, Kubernetes, Red Hat, or AI infrastructure technologies.

Required education

• University education (Master's degree)
• Postgraduate (Doctorate)

What will you do

• Deploy, configure, and support large-scale High Performance Computing (HPC) and AI infrastructure solutions for enterprise customers.
• Work across the full technology stack, including data centre infrastructure, networking, storage systems, Kubernetes platforms, and GPU environments.
• Lead the integration, validation, testing, and troubleshooting of complex HPC and AI solutions to ensure successful deployments.
• Implement and optimize AI orchestration, MLOps platforms, GPU resource management,and AI/ML workloads in production environments.
• Collaborate closely with customers, technology partners, and internal project teams throughout the entire project lifecycle, from installation to production handover.
• Provide technical expertise and make informed decisions to resolve deployment challenges and ensure project success.